Data Engineer (m/f/d) - 100%

As a Senior Data Engineer at Diagnostics Operations Rotkreuz, you will lead the development and optimization of a robust data infrastructure that drives our DOD operations and data products. In this strategic role, you’ll work closely with multidisciplinary teams - including data scientists, subject matter experts, and fellow data engineers - to design, transform, and enhance data assets that are foundational to our advanced modelling approaches. You’ll take a lead role in shaping and scaling data product standards across DIA Global Operations, ensuring alignment, quality, and impact at the organisational level. Beyond hands-on contributions, you’ll provide technical guidance to juniors and fellow data engineers alike, establishing best practices and fostering a culture of innovation.

The perfect candidate

The perfect candidate has a Master’s degree in Computer Science or Data Engineering and brings over 5 years‘ experience in data engineering with a track record in architecting and scaling large data systems. Also we are looking for someone with proven experience in building and managing data pipelines and products.

• Lead Data Pipelines & Storage: Design and build scalable data pipelines for real-time and batch processing. Drive architectural decisions and long-term planning for scalable, FAIR data products.
  
• High-Quality Data Products: Create high-quality data products adhering to FAIR principles. Address complex challenges, ensure compliance, and make strategic decisions to shape
  
• data roadmaps.
  
• Collaboration & Integration: Model data landscapes, acquire data extracts, and define secure exchange methods in collaboration with experts and cross-functional teams.
  
• Data Ingestion & Processing: Ingest and process data from diverse sources into Big Data platforms (e.g., Snowflake). Develop ERDs and reusable pipelines for advanced analytics.
  
• Technical Guidance & Governance: Contribute to our Data Mesh Engineering Collective to establish data governance standards, ensure regulatory compliance and data security. Mentor others and promote best practices.
  
• Information Security & Infrastructure Collaboration: Ensure adherence to information security standards. Collaborate with infrastructure teams for tailored tech stacks. Make independent decisions on data strategies.
  
• Innovation & Knowledge Sharing: Shape the data engineering roadmap and set standards for data quality and governance. Proactively share best practices.
  
• Technical Proficiency: Maintain proficiency in data engineering tech stacks, data quality, and observability tools (e.g., Ataccama, Monte Carlo).
  
• Adherence to Standards: Ensure compliance with relevant guidelines and data governance standards. Develop long-term enterprise tools.
  

• Master�s degree in Computer Science, Data Engineering, or a related field.
  
• Over 5 years in data engineering with a track record in architecting and scaling large data systems.
  
• 5+ years of experience in leading and mentoring data engineers.
  
• Proven experience in building and managing data pipelines and products.
  
• Skilled in handling structured, semi-structured, and unstructured data.
  
• Proficiency in Python, Java, SQL, or Scala, and experience with big data technologies (e.g., Hadoop, Spark).
  
• Expertise in multiple cloud platforms (AWS, Azure, GCP) and data warehousing technologies (preferably Snowflake).
  
• Deep understanding of Information Security to ensure compliant handling and management of process data.
  
• Familiarity with data modeling and ETL tools.
  
• Knowledge of version control systems like Git and CI/CD pipelines.
  
• Proficiency in implementing robust testing practices and monitoring pipelines for performance, reliability, and data quality.
  
• Client-facing project experience.
  
• Proven ability to communicate complex solutions to varied technical audiences.
  
• Strong organizational and interpersonal skills for delivering results and optimizing resources.
  
• Ability to work independently and collaboratively within a team environment.
  
• Strong ability to influence
  

• 3+ years of experience in the pharmaceutical or healthcare industry.
  
• Experience with REST APIs and integrating data from various sources.
  
• Knowledge of regulatory requirements (e.g., GMP, FDA) and Quality systems.
  
• Experience with AI-driven data solutions and machine learning pipelines.
  
• Experience with ML platforms (e.g., Dataiku).
  
• Knowledge of software engineering best practices (code reviews, testing, maintainability).
  

Job Type: 100%

Work Location: On the road